Research and Development of Signal Processing Algorithms in MIMO Systems Using Space-Time Codes

With the advancement of digital radio communication systems, there is a growing demand for enhanced spectral efficiency in mobile and hybrid radio systems and networks. To meet these requirements, Multiple-Input Multiple-Output (MIMO) technology is extensively employed in modern radio communication systems. The use of multiple transmitting and receiving antennas in MIMO systems imposes stringent performance requirements on signal processing algorithms. Consequently, the development of fast and efficient signal processing algorithms is a task of significant relevance. The aim of this study is to analyze and optimize space-time coding techniques and signal processing algorithms for MIMO systems. The research focuses on developing an algorithm that ensures the required level of performance while significantly reducing computational complexity. Methods . This study utilizes numerical simulation methods within the MATLAB environment to compare the performance of various signal processing algorithms in MIMO systems over a fading channel. Results. In addressing the research objectives, the principles of constructing space-time code matrices for different coding methods were examined, and coherent signal demodulation techniques were analyzed. Based on this analysis, an algorithm with reduced computational complexity is proposed. A key element of scientific novelty of this work lies in the development and application of a novel approach to approximate the inverse channel matrix, which is a computationally expensive operation, particularly for high-dimensional matrices in coherent demodulation algorithms. This new approach is based on the combined use of the iterative Jacobi method and the Neumann series expansion for the approximation of the matrix inverse. Practical significance. The developed algorithm can be utilized in the design of MIMO systems with a large number of transmitting and receiving antennas, as well as in the application of non-orthogonal coding schemes to increase the coding rate. In such systems, conventional demodulation methods require significant computational resources for inverting the channel matrix, which limits real-world performance. The proposed algorithm mitigates this bottleneck, enabling more practical implementations.